Matrix/TensorFlow for Baby Hawk

Integrating Baby Hawk (Gemini 1.5) with Matrix Group Chat and TensorFlow in Docker

This tutorial guides you through integrating Gemini 1.5 API to interact in various Matrix rooms, leveraging a TensorFlow model running in a Docker container equipped with Jupyter Notebook.

Prerequisites

• Running instance of Baby Hawk's Gemini 1.5 API on ailounge.xyz
• TensorFlow instance running in Docker with Jupyter Notebook
• Matrix Synapse server running in Docker
• Basic knowledge of Docker, Python, Jupyter Notebooks, and Matrix
• Domain names set up for matrix.ailounge.xyz and Jupyter accessed via ailounge.xyz

Step 1: Set Up Matrix Synapse Server using Docker

1. Install Docker and Docker Compose: If not already installed, install Docker and Docker Compose.
2. Create a Docker Compose File (docker-compose.yml):

version: '3'
services:
  synapse:
    image: matrixdotorg/synapse:latest
    restart: always
    environment:
      - SYNAPSE_SERVER_NAME=matrix.ailounge.xyz
      - SYNAPSE_REPORT_STATS=yes  
    volumes:
      - ./data:/data 
    ports:
      - 8008:8008
      - 8448:8448

1. Run Docker Compose:

docker-compose up -d

1. Register Admin User: Follow instructions in the container logs to register an admin user.

Step 2: Secure Jupyter Notebook and Matrix Synapse with SSL Using Certbot

1. Install Certbot:

sudo apt install certbot

1. Obtain Certificates:

sudo certbot certonly --standalone -d ailounge.xyz -d matrix.ailounge.xyz

1. Configure Jupyter to Use SSL:

Add SSL configuration to the Docker command for Jupyter:

--NotebookApp.certfile=/etc/ssl/certs/jupyter.crt --NotebookApp.keyfile=/etc/ssl/private/jupyter.key

1. Configure Matrix Synapse to Use SSL:

Update Synapse's configuration to use the obtained SSL certificates.

Step 3: Configure and Run Baby Hawk's Gemini 1.5 API

Ensure the API endpoint for Baby Hawk is publicly accessible and secured with SSL.

Step 4: Implement Continuous Learning with TensorFlow in Docker

1. Expose Ports: Ensure the TensorFlow container exposes port 8888.
2. Install Libraries: Within the container, install libraries needed for integration, e.g., matrix-nio.
3. Access MongoDB: Configure access to MongoDB for data storage.
4. Collect & Preprocess Data: Use Jupyter Notebook for data handling.
5. Retrain Model: Continuously retrain the TensorFlow model based on new data.
6. Update API: Update the Baby Hawk API to utilize the retrained models.

Step 5: Create and Run a Matrix Bot for Integration

Script a bot that uses Baby Hawk's API to interact within Matrix rooms.

DNS Configuration

• Add A records for ailounge.xyz and matrix.ailounge.xyz.
• Configure necessary SRV records for Matrix services.

Important Notes

• Ensure proper networking between containers.
• Protect sensitive data and credentials.
• Experiment with model training and architecture.

Credits

This tutorial was collaboratively created by [Your Names], Google's Gemini Advanced AI, and ChatGPT from OpenAI.